[dajiaohuang]

Fixes #3195.

Invalid-image retries now try each dataset index at most once per request, preserving the first preference for the last successful sample while continuing if that sample has also become invalid. Exhaustion raises a clear RuntimeError instead of overrunning the dataset or looping forever. A pipeline result of None is treated as a rejected sample and is not recorded as successful. Empty/out-of-range input remains an IndexError; valid negative indices are normalized.

Replaced the AST/class extraction test with normal importlib.import_module loading of the complete source module. The fixture uses actual PyTorch/NumPy and the source-tree exception/array helper modules, with unavailable MMDet/MMCV/native-extension/training helpers isolated through explicit module stubs. This verifies the real imported wrapper but does not claim a full framework training run.

Validation:

• 9 focused pytest cases pass: initial consecutive failures, all invalid, known-good fallback, fallback becoming invalid, pipeline None, all pipeline rejections, out-of-range input, negative input and empty data.
• Against the previous PR head, 7 cases fail and 2 existing-success cases pass; the refined implementation passes all 9.
• Black check and git diff --check pass.
• Pytest plugin auto-loading was disabled because an unrelated installed Home Assistant plugin imports Unix-only fcntl on this Windows host. No target plugin was bypassed for these focused wrapper tests.
• Full MMDet/MMCV training integration, the native Deep Lake extension and full repository CI were not run locally.

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📝 Walkthrough

Walkthrough

The MMDet dataset wrapper now advances past consecutive invalid samples until it reads a valid sample. It records the index after a successful read. A new regression test checks this behavior.

Changes

MMDet invalid-sample retry

Layer / File(s)	Summary
Retry index and regression test python/deeplake/integrations/mmdet/mmdet_dataset_.py, python/tests/test_mmdet_invalid_sample_loop.py	The wrapper advances past invalid samples until one succeeds, then records the successful index. The test checks reads at indices 0, 1, and 2.

Priority: ➖ Normal

Estimated code review effort: 2 (Simple) | ~10 minutes

Change: Bug fix · Severity of issue fixed: Medium

Merge Risk: 🟡 Moderate · up to 8bb9a

The retry fix handles invalid images that appear before the first good sample. Two gaps remain. A sample the pipeline rejects can still become the fallback, so later reads can return empty results. A fallback image that later fails can hang data loading indefinitely. Fix both before merging.

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 6 functions across 2 files.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Linked Issues check	✅ Passed	Issue #3195 requires MMDetTorchDataset.getitem to advance past consecutive InvalidImageError samples and update last_successful_index only after successful conversion. The pull request implements …
Out of Scope Changes check	✅ Passed	The changes are limited to the MMDet retry logic and a focused regression test for issue #3195. The test directly verifies the requested retry and successful-index behavior. No unrelated change is ide…
Title check	✅ Passed	The title clearly and concisely describes the main change: advancing past invalid MMDet images.
Description check	✅ Passed	The description explains the bug fix, retry behavior, error handling, tests, and validation limits. It does not include the template headings or impact checkbox, but the core required information is c…

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Actionable comments posted: 2

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• 🪄 Fix CodeRabbit comments on this PR

🤖 Prompt to fix review comments

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Inline comments:
Review comments at @python/deeplake/integrations/mmdet/mmdet_dataset_.py:
- Line 434: Update the fallback selection in __getitem__ so a failing
last_successful_index is not selected repeatedly; advance to another index and
enforce a bounded retry policy that returns an error when no valid index is
found.
- Line 427: Update the MMDet sample pipeline handling around
last_successful_index so a None result is treated as rejection: retry the sample
without recording idx, and update last_successful_index only after the pipeline
returns a valid sample.

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ℹ️ Review info

⚙️ Run configuration

Configuration used: Organization UI

Review profile: CHILL

Plan: Advanced

Run ID: ff43fd2d-88ce-4c68-b453-f6eabb23c7e4

📥 Commits

Reviewing files that changed from the base of the PR and between f432041 and 8bb9a84.

📒 Files selected for processing (2)

• python/deeplake/integrations/mmdet/mmdet_dataset_.py
• python/tests/test_mmdet_invalid_sample_loop.py

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[khustup2]

Same questions as #3194:

1. Reproduction for the infinite retry.
2. Bound the loop when every image is invalid; today idx runs past the dataset end.
3. Replace the ast/exec test with a normal import.

[dajiaohuang]

Replaced AST/class extraction with a normal import of the full source module, and bounded retry handling to try each index at most once. It still prefers the known successful sample, but continues when that fallback also fails; complete exhaustion raises a clear RuntimeError. Pipeline None is now rejection and cannot update last_successful_index.

All 9 focused tests pass. The previous head fails 7 of them, including all-invalid exhaustion, a formerly good fallback becoming invalid, and pipeline rejection. Black and diff checks pass. The fixture uses actual PyTorch/NumPy and the source-tree exception helper, but isolates unavailable MMDet/MMCV/native/training dependencies; no full framework integration pass is claimed.

[khustup2]

Same as #3194: bounded retries, clear RuntimeError on exhaustion, IndexError preserved, real module import in the tests. The None-as-rejection change matches mmdet's CustomDataset behavior.